Accuracy metric for Clustering
You can compute &quot;Silhouette Coefficient&quot; for your aim. Its values mean:

1: Means clusters are well apart from each other and clearly distinguished.
0: Means clusters are indifferent, or we can say that the distance between clusters is not significant.
-1: Means clusters are assigned in the wrong way.

Also other measures such as purity and mutual information can be possible by ``computing an external criterion that evaluates how well the clustering matches the gold standard classes.''.